| Title |
An Improved Biometrics-Based Authentication Scheme for Telecare Medical Information Systems
|
|---|---|
| Published in |
Journal of Medical Systems, February 2015
|
| DOI | 10.1007/s10916-015-0194-6 |
| Pubmed ID | |
| Authors |
Dianli Guo, Qiaoyan Wen, Wenmin Li, Hua Zhang, Zhengping Jin |
| Abstract |
Telecare medical information system (TMIS) offers healthcare delivery services and patients can acquire their desired medical services conveniently through public networks. The protection of patients' privacy and data confidentiality are significant. Very recently, Mishra et al. proposed a biometrics-based authentication scheme for telecare medical information system. Their scheme can protect user privacy and is believed to resist a range of network attacks. In this paper, we analyze Mishra et al.'s scheme and identify that their scheme is insecure to against known session key attack and impersonation attack. Thereby, we present a modified biometrics-based authentication scheme for TMIS to eliminate the aforementioned faults. Besides, we demonstrate the completeness of the proposed sche-me through BAN-logic. Compared to the related schemes, our protocol can provide stronger security and it is more practical. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 19 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Lecturer | 3 | 16% |
| Student > Master | 3 | 16% |
| Student > Ph. D. Student | 3 | 16% |
| Student > Bachelor | 2 | 11% |
| Student > Doctoral Student | 1 | 5% |
| Other | 2 | 11% |
| Unknown | 5 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 4 | 21% |
| Business, Management and Accounting | 2 | 11% |
| Nursing and Health Professions | 2 | 11% |
| Social Sciences | 2 | 11% |
| Agricultural and Biological Sciences | 1 | 5% |
| Other | 3 | 16% |
| Unknown | 5 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 February 2015.
All research outputs
#18,401,956
of 22,793,427 outputs
Outputs from Journal of Medical Systems
#807
of 1,149 outputs
Outputs of similar age
#257,763
of 353,703 outputs
Outputs of similar age from Journal of Medical Systems
#15
of 24 outputs
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